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Section 1 Landscape Planning 1 Chapter 1 Protected Areas 3 Murat Özyavuz Chapter 2 Land Use/Cover Classification Techniques Using Optical Remotely Sensed Data in Landscape Planning 21

  Edited by Murat Özyavuz 

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Landscape Planning, Edited by Murat Özyavuz

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Section 1 Landscape Planning 1

Chapter 1 Protected Areas 3

Murat Özyavuz Chapter 2 Land Use/Cover Classification Techniques Using

Optical Remotely Sensed Data in Landscape Planning 21

Onur Şatır and Süha Berberoğlu Chapter 3 GIS in Landscape Planning 55

Matthias Pietsch Chapter 4 An Approach to Landscape Planning in Borders 85

Gloria Aponte Chapter 5 Urban Green Space System Planning 107

Bayram Cemil Bilgili and Ercan Gökyer Chapter 6 Tourism Planning in

Rural Areas and Organization Possibilities 123

Tuğba Kiper and Gülen Özdemir Chapter 7 Agriculture and Rurality as

Constructor of Sustainable Cultural Landscape 151

Juan Gastó, Diego Subercaseaux, Leonardo Vera and Tonci Tomic Chapter 8 Residents’ Perceptions of and

Attitudes Toward Sustainable Tourism Planning and Management in Amasra (Turkey) 177

Bülent Cengiz Chapter 9 Woody Plants in

Landscape Planning and Landscape Design 199

Viera Paganová and Zuzana Jureková

An Opportunity to Landscape Planning Improvement 217

Maria José Curado and Teresa Portela Marques Chapter 11 Ecological Landscape Planning,

with a Focus on the Coastal Zone 233

Canan Cengiz

Section 2 Landscape Design 249

Chapter 12 Landscape Perception 251

Isil Cakci Kaymaz Chapter 13 Urban Landscape Design 277

Murat Z Memlük Chapter 14 Irrigation 299

Mehmet Sener Chapter 15 Private Plantation Techniques 319

Ömer Lütfü Çorbacı and Murat Ertekin Chapter 16 Xeriscape in Landscape Design 353

Ayten Özyavuz and Murat Özyavuz

Preface

The purpose of this book is to reveal of the landscape planning and design in recent years.  For  this  purpose,  chapters  were  selected  on  the  topics  of  different  landscape architecture study. Landscape architecture is the design of outdoor and public spaces 

to achieve environmental, socio‐behavioral, and/or aesthetic outcomes. It involves the systematic  investigation  of  existing  social,  ecological,  and  geological  conditions  and processes  in  the  landscape,  and  the  design  of  interventions  that  will  produce  the desired  outcome.  The  scope  of  the  profession  includes:  urban  design;  site  planning; town  or  urban  planning;  environmental  restoration;  parks  and  recreation  planning; visual resource management; green infrastructure planning and provision; and private estate  and  residence  landscape  master  planning  and  design  ‐  all  at  varying  scales  of design,  planning  and  management.  Landscape  planning  is  the  key  planning instrument  for  nature  conservation  and  landscape  management.  Apart  from  the landscape  plans  at  the  local  level,  i.e.  municipal  level,  there  are  landscape  structure plans  (Landschaftsrahmenplane)  at  the  district  or  planning  region  level (Regierungsbezirk,  Landkreis,  Planungsregion)  and  the  regional  landscape programme  (Landschaftsprogramm)  for  an  entire  regional  state  (Land).  The  local landscape plans (Artliche Landschaftsplane) are based on the specifications contained 

in the regional landscape programme and the landscape structure plans. At all levels landscape planning makes an important long‐term contribution to the conservation of natural  resources.  It  not  only  addresses  the  narrower  areas  of  particularly  valuable protected  sites,  but  also  devises  strategies  for  full‐coverage,  sustainable  conservation and the long‐term development of nature and landscapes. 

This  book  is  for  landscape  architects  and  other  planning  professions.  Theoretical foundations,  theories,  methods,  and  applications  will  be  essential  parts  of  this reference  book.  In  addition,  this  book  addresses  several  very  different  subjects  of study;  landscape  management,  biodiversity,  landscape  restoration,  landscape  design, and urban design related to theory, practice and the results will be covered. Due to the varied  usage  of  the  term  Planning/Landscape  Planning,  the  intended  readership  for this  book  is  a  broad  audience  including  environmentalists,  landscape  architects, architects,  environmentalists,  botanists,  urban  and  regional  planners,  government agencies,  non‐governmental  organizations,  agricultural  organizations,  students  at  all levels, research organizations, international organizations and all interested parties. 

I would like to express my deep sense of gratitude and indebtedness to all the authors for  their  valuable  contributions  and  also  to  the  researchers  who  actually  performed experiments  and  reported  their  findings.  I  must  confess  that  it  had  been  a  rare privilege for me to be associated with InTech publishers. Thanks is the least word to offer  to  Ms.  Marina  Jozipovic,  Ms.  Sasa  Leporic  and  Mr.  Metin  Ertufan,  Intech Publishing  Process  Managers,  yet  I  shall  avail  this  opportunity  to  extend  my  sincere gratitude  for  their  help  and  co‐operation  at  various  phases  of  book  publication.  Last but not least I express my sincere thanks and affection to my wife Ayten Özyavuz and 

Section 1

Landscape Planning

1

Protected Areas

Murat Özyavuz

Namık Kemal University, Faculty of Agriculture,

Department of Landscape Architecture

Turkey

1 Introduction

Protected areas are essential for biodiversity conservation They are the cornerstones of virtually all national and international conservation strategies, set aside to maintain functioning natural ecosystems, to act as refuges for species and to maintain ecological processes that cannot survive in most intensely managed landscapes and seascapes Protected areas act as benchmarks against which we understand human interactions with the natural world Today they are often the only hope we have of stopping many threatened

or endemic species from becoming extinct (Dudley, 2008)

The original intent of the IUCN Protected Area Management Categories system was to create a common understanding of protected areas, both within and between countries This

is set out in the introduction to the Guidelines by the then Chair of CNPPA (Commission on National Parks and Protected Areas, now known as the World Commission on Protected

Areas), P.H.C (Bing) Lucas who wrote: “These guidelines have a special significance as they are intended for everyone involved in protected areas, providing a common language by which managers, planners, researchers, politicians and citizens groups in all countries can exchange information and views” (The International Union For Conservation of Nature [IUCN], 1994)

IUCN defines a protected area as:

“An area of land and/or sea especially dedicated to the protection of biological diversity, and of natural and associated cultural resources, and managed through legal or other effective means”

Category II

Protected area managed mainly for ecosystem protection and recreation (National Park)

A natural area of land and/or sea designated to (a) protect the ecological integrity of one or more ecosystems for present and future generations; (b) exclude exploitation or occupation inimical to the purposes of the area; and (c) provide foundation for spiritual, scientific, educational, recreational, and visitor opportunities all of which must be environmentally and culturally compatible

Category III

Protected area managed mainly for conservation of specific natural features (Natural Monument)

An area containing one or more specific natural or natural/cultural feature which is of outstanding or unique value because of its inherent rarity, representative or aesthetic qualities or cultural significance

Category IV

Protected area managed mainly for conservation through management intervention

An area of land and/or sea subject to active intervention for management purposes so as to ensure the maintenance of habitats and/or to meet the requirements of specific species

is vital to the protection, maintenance and evolution of such an area

It is sometimes assumed that protected areas must be in conflict with the rights and traditions of indigenous and other traditional peoples on their terrestrial, coastal/marine, or freshwater domains In reality, where indigenous peoples are interested in the conservation and traditional use of their lands, territories, waters, coastal seas and other resources, and their fundamental human rights are accorded, conflicts need not arise between those peoples’ rights and interests, and protected area objectives Moreover, formal protected areas can provide a means to recognize and guarantee the efforts of many communities of indigenous and other traditional peoples who have long protected certain areas, such as sacred groves and mountains, through their own cultures (IUCN, 2000)

Protected Areas 5 Based on the advice in the protected areas management categories, on established WWF and IUCN policies on indigenous peoples and conservation, and on conclusions and recommendations of the IV World Congress on National Parks and Protected Areas, the two organizations, WWF and IUCN/WCPA, have adopted principles and guidelines concerning indigenous rights and knowledge systems, consultation processes, agreements between conservation institutions, decentralization, local participation, transparency, accountability, sharing benefits and international responsibility The five principles are as follows (IUCN, 2000):

Principle 1

Indigenous and other traditional peoples have long associations with nature and a deep understanding of it Often they have made significant contributions to the maintenance of many of the earth’s most fragile ecosystems, through their traditional sustainable resource use practices and culture-based respect for nature Therefore, there should be no inherent conflict between the objectives of protected areas and the existence, within and around their borders, of indigenous and other traditional peoples

Principle 2

Agreements drawn up between conservation institutions, including protected area management agencies, and indigenous and other traditional peoples for the establishment and management of protected areas affecting their lands, territories, waters, coastal seas and other resources should be based on full respect for the rights of indigenous and other traditional peoples to traditional, sustainable use of their lands, territories, waters, coastal seas and other resources

Principle 3

The principles of decentralization, participation, transparency and accountability should be taken into account in all matters pertaining to the mutual interests of protected areas and indigenous and other traditional peoples

Principle 4

Indigenous and other traditional peoples should be able to share fully and equitably in the benefits associated with protected areas, with due recognition to the rights of other legitimate stakeholders

Principle 5

The rights of indigenous and other traditional peoples in connection with protected areas are often an international responsibility, since many of the lands, territories, waters, coastal seas and other resources which they own or otherwise occupy or use cross national boundaries, as indeed do many of the ecosystems in need of protection

Financial Planning In Protected Areas

A financial plan is a tool which helps to determine the protected area’s funding requirements, and to match income sources with those needs Financial planning differs from a budget in that, in addition to identifying how much money is needed for different types of activities, it also identifies the most appropriate funding sources for short, medium, and long-term needs (IUCN, 2001)

Seven steps are required to develop a financial plan:

1 define protected area goals and objectives;

2 identify the existing customer base;

3 list financial resources and demands on these resources;

4 identify new customers and relative levels of use versus contribution;

5 identify mechanisms to capture income from customers;

6 evaluate the feasibility of the proposed mechanisms; and

7 clearly state the financial plan

Protected Area Economic Benefits

A protected area also provides its customers with a number of goods and services These could include goods such as thatching grasses, wild berries and genetic materials, and services such as biodiversity conservation, crop pollination, water purification, game viewing and recreational opportunities Such goods and services provide society with a stream of benefits from the existence of the protected area The benefits can be divided into two categories: so-called ‘use’ (comprising direct and indirect values) and ‘non-use’ (comprising option, bequest and existence values) benefits (IUCN, 2001)

The structure of an ecosystem includes the species contained therein, their mass, their arrangement, and other relevant information This is the ecosystem’s standing stock—nature’s free goods The functions of an ecosystem, on the other hand, are characterized by the ways in which the components of the system interact They provide nature’s free services, maintaining clean air, pure water, a green earth, and a balance of creatures, enabling humans to obtain food, fiber, energy, and other material needs for survival Evaluating the contribution of ecosystem functioning to human welfare is a complex task, involving human social values and political factors

Direct use values of protected areas derive from the actual use of the protected area for such

activities as recreation, tourism, the harvesting of various natural or cultural resources,

hunting and fishing, and educational services Conversely, indirect use value sderive from the

goods and services not directly provided by visits to protected areas Notably these include ecological functions such as watershed protection, the provision of breeding or feeding habitat, climatic stabilization and nutrient recycling Such indirect use values are often widespread and significant, but have been under-valued, if not totally ignored by past economic valuation systems Indeed, most of the studies that have attempted to value these indirect goods and services have found that they have far greater value than the more easily measured direct values (Figure 1)

Fig 1 Total economic benefit of protected areas (IUCN, 2001)

Protected Areas 7

Option value refers to the potential for individuals or society to use the protected area in the

future For example, many people value a particular protected area even though they have never visited the park, but feel that at some future date they might like to do so

Bequest value relates to the benefit of knowing that others (e.g children or grandchildren)

benefit or will benefit from the goods and services provided by the protected area Finally,

existence value derives from the benefit of knowing that the protected area exists and

provides valuable goods and services Even if they do not plan on ever visiting a particular protected area or protected area system, many people attach value to the more existence of such sites (e.g for the indirect benefits they provide or as sources of local or national pride) (IUCN, 2001)

2 Protected areas in Turkey

In terms of biodiversity, Turkey is one of the richest countries in Europe and the Middle East, and ranks the ninth on the European Continent in this respect There are a number of different ecological regions each with its own endemic species and natural ecosystems The richness of biodiversity in Turkey is expressed in its 120 mammals, more than 400 bird species, 130 reptiles, and nearly 500 fish species The diversity of the geographic formations

of Turkey and its location at the intersection of two important Vavilovian gene centers (the Mediterranean and the Near Eastern) are the reasons for high endemism and genetic diversity (Ministry of Environment, 2002)

There have been various types of habitats formed in the earth since the beginning of the world and existence of the living beings Human beings, animals, plants and microorganisms have been surviving in the ecosystems together for many years together with the non-living beings, like water, air, soil, rock and climatologically factors However, due to technological developments starting from 1960’s, there have been significant adverse impacts on the nature Man can survive less dependent on the surrounding factors and has the ability to easily change the environmental factors with his technological power The ecological balances have been greatly degraded due to increase in populations and rapidly developing technologies In this regard, Turkey is relatively lucky when compared to the most of the countries in Europe and America In Turkey, there are still number of ecosystems where natural balance has not been completely degraded and we still have a rich biodiversity throughout Turkey

Turkey is home to 75% of the plant species that exist on the European continent, and one third of these species are endemic plants The rich flora of Turkey includes more than 9,000 plant species and more than 500 bulbous plants This flora, with a high endemism ratio, is also rich in medicinal and aromatic plants (Ministry of Environment, 2002) Most of the endemic plant species are found in the Taurus Mountains, the Nur Mountains and the Eastern Black Sea Coast (Ministry of Environment, 2001)

Located on the migration routes of many birds, Turkey is a key country for many bird species 454 bird species have been sited Several of its species are globally under threat (Ministry of Environment, 2002) Turkish wetlands are of crucial importance for many breeding species of birds

There are 472 fish species in Turkey and 50 of these are at risk of extinction Some 192 freshwater fish species belonging to 26 different families have been identified (Ministry of Environment,2002)

Approximately 3,000 plant and animal species have been identified in Turkey’s seas (Ministry of Environment, 2001) There are about 20 species of mammals including the Mediterranean monk seal, whales and dolphins with mostly decreasing populations The Turkish Straits and the Sea of Marmara form a special ecosystem (an ecotone) between the Mediterranean and the Black Sea The Aegean Sea is especially important for the

endangered Mediterranean monk seal (Monachus monachus), which is considered to be one

of the 12 most endangered species in the world Less than 50 specimens inhabit the coasts of Turkey (Ministry of Environment, 2001) The Aegean Sea and its islands contain numerous

microhabitats (Posidonia oceanica and Cystoseira species) that play an important role in the

sustainability of the ecosystem (Ministry of Environment, 2002)

Turkey has accepted the Action Plan (1989 and 1999) for the conservation of Mediterranean marine turtles within the framework of the Barcelona Convention Several breeding habitats of marine turtles, including Dalyan, Fethiye, Patara, Goksu Delta, and Belek, were declared as Specially Protected Areas in 1988 and 1990 The Ministry of Environment established the Marine Turtles National Commission and the Marine Turtles Scientific Commission for the coordination of activities towards the protection of the two species Turkey also accepted the action plan for the conservation of the Mediterranean monk seal, again developed in the framework of the Barcelona Convention (Ministry of Environment, 2002) In this context, Turkey has signed many international conventions and agreements

In this context, Turkey has signed many international conventions These conventions are; International Conventions and Protocols on Nature Protection Ratified by Turkey

 Convention on Biodiversity Conservation (Rio Convention) (1997)

 Cartagena Protocol (2004)

 CITES (1996)

 Barcelona Convention (1988)

 Bucharest Convention (1994)

 Protection of Cultural and National Heritage (1983)

 Convention on Combating Erosion (1998)

 European Landscape Convention (2000)

Protected Areas 9

Conservation Status Number Related Law

National park 41 Law on National Parks

Nature conservation area 31 Law on National Parks

Natural monument 106 Law on National Parks

Nature park 41 Law on National Parks

Wild life reserve areas 79 Law on Terrestrial Hunting

Conservation forest 57 Law on Forest

Genetic conservation areas 214 Law on Forest

Seed stands 339 Law on Forest

Specially protected areas (SPAs) 14 Law on Environment

Natural sites 947 Law on Conservation of Cultural And

Natural Heritage

Ramsar sites 13 Ramsar Convention

By-law on Conservation of Wetlands

Biosphere Reserve 1 Law on National Parks -Law on Forest

Table 1 Protected areas which identified by the Ministry of Forest and Water

Conservation Staus Number Archaeological Site 4,920

National Parks

A national park refers to an plot of land set aside by a national government and usually designated as an area free of development Often, national parks include pristine wilderness areas or other pieces of environmental heritage which the nation has deemed worthy of preservation In the United States, national parks also include historic areas and monuments

to scientific achievement

Prepared by the IUCN classification of protected areas, national parks are in Categories 2 Definition of this category is below;

'Natural area of land and/or sea, designated to (a) protect the ecological integrity of one or more ecosystems for present and future generations, (b) exclude exploitation or occupation inimical to the purposes of designation of the area and (c) provide a foundation for spiritual, scientific, educational, recreational and visitor opportunities, all of which must be environmentally and culturally compatible

Management Objectives of This Category

 To protect natural and scenic areas of national and international significance for spiritual, scientific, educational, recreational or tourist purposes

 To perpetuate, in as natural a state as possible, representative examples of physiographic regions, biotic communities, genetic resources, and species, to provide ecological stability and diversity;

 To manage visitor use for inspirational, educational, cultural and recreational purposes

at a level which will maintain the area in a natural or near natural state

 To eliminate and thereafter prevent exploitation or occupation inimical to the purposes

Guidance for Selection

 The area should contain a representative sample of major natural regions, features

or scenery, where plant and animal species, habitats and geomorphological sites are of special spiritual, scientific, educational, recreational and touristic significance

 The area should be large enough to contain one or more entire ecosystems materially altered by current human occupation or exploitation

National parks are natural areas that provide transcendental, adventure and educational experiences One management goal, however, is to take into account the needs of indigenous people In this way, parks serve multiple constituencies that have sometimes been at loggerheads (Weeks and Mehta, 2004)

National Parks Law in Turkey, scientific and aesthetic terms, national and international rare, natural and cultural resource values and conservation, recreation and tourism will have the values of nature

The purpose of this Law is specified as the “identification of areas which possess values of national and international importance, as national park, nature park, nature monument, and nature protection area, and the protection, enhancement and management of these areas without degrading their values and characteristics” There are 43 national parks in Turkey (Figure 2)

Protected Areas 11

Fig 2 National parks in Turkey

The first national park in Turkey was established in 1958 (The Yozgat Pine Grove National Park) (Figure 3) Some of these parks, which were initially established for archaeological and

historical purposes, are at the same time rich habitats where biological diversity is being protected

Fig 3 The Yozgat Pine Grove National Park, Turkey (www.milliparklar.gov.tr)

National Parks are defined as recreation and tourism areas which are rare in terms of scientific and scenic perspective in nature and are important for the conservation of the

natural and cultural resource values (Yücel, 1995) These areas are in different regions of Turkey and were assigned as national parks at various dates and with various purposes; they are now under protective control and are kept open for public use (Güçlü and Karahan, 2008)

Some information and resource values of these national parks are given below (Table 1)

National Park Area (ha) Date Resource Value

The Yozgat Pine Grove National

Natural Pinus sp (residual

forest)

Karatepe Aslantaş National Park 7715 1958 Flora, visual landscape, historical value

Soğuksu National Park 1195 1959

Geological and geomorphologic value, thermal water

Bird Paradise National Park 24047 1959 Fauna, especially bird species

Uludağ National Park 12372 1961 Flora and fauna

Yedigöller (Sevenlakes) National

Dilek Peninsula National Park 27675 1966 Flora, fauna, wetlands

Spil Mountain National Park 6693,5 1968

Geological value, flora, historic and mythological

value

Kızıldağ National Park 59400 1969 Geological value, flora

Termessos National Park 6702 1970 Ancient city, geological value,

Munzur Valley National Park 42000 1971 geomorphologic value Streams, flora, fauna,

Olympos National Park 34425 1972 Archeological residual, flora

Gelibolu Peninsula Historical

Historical war, geological and geomorphologic value

Köprülü Canyon National Park 36614 1973 Archeological residual, geological value

Başkomutan Historical National

Park 40742 1981 Cultural and geological value Göreme Historical National Park 9572 1986 geomorphologic value Historical settlement,

Altındere Valley National Park 4800 1987 Cultural value, landscape,

Boğazköy-Alacahöyük Historical

National Park 2634 1988 Archeological residual

Kazdağları National Park 21463 1993 Flora, fauna, biodiversity,

Kaçkar Mountain National Park 51550 1994

Geological and geomorphologic value, flora

and fauna

Hattila Valley National Park 16988 1994 geomorphologic value, flora Geological and

and fauna

Altınbeşik Cavern National Park 1156 1994 geomorphologic value Geological and

Karagöl – Sahara National Park 3766 1994 Hydrographic structure, vegetation

Aladağlar National Park 54 524 1995 Landscape, waterfall

Honaz Mountain National Park 9616 1995 Geological and

geomorphologic value, flora

Troya Historical National Park 13350 1996 Geomorphologic value,

historical residual

Marmaris National Park 33350 1996 Geomorphologic value, flora

and fauna

Saklıkent National Park 12390 1996 Flora, fauna, hydrological geomorphologic value

Küre Mountain National Park 37000 2000

Natural forest, biodiversity, geological and geomorphologic value

Sarıkamış-Allahuekber Mountain

National Park 22980 2004 Historical value, fauna Ağrı Mountain National Park 87 380 2004 Geomorphologic value

Gala Lake National Park 6090 2005 ecosystem, bird species Wetland and forest

Sultan Sazlığı National Park 24523 2006 Wetland ecosystem, bird

species

Tek Tek Mountain National Park 19335 2007 Geomorphologic and

historical value, fauna

İğneada Longos Forest National

Wetland and alluvial forest ecosystem, lagoon, flora,

fauna

Yumurtalık Lagoon National Park 16 430 2008 Lagoon, swamp, sand dune

Nenehatun National Park 387 2009 Historical value

Table 3 National Parks in Turkey

3 The case study, Iğneada Longos forest national park

The Igneada Longos Forests National Park, located on the Black Sea coast 15 km from the Turkish-Bulgarian border, is positioned between the northern latitudes 41’ 44’ 43’ and 41’ 58’ 27’ and the eastern longitudes 27’ 44’ 52’ and 28’ 3’ 17’.The Igneada area includes different kinds of ecosystems (sand dunes, wetlands, longos (flooded alluvial) forests, deciduous forests, and many streams) and a wide range of biodiversity; these characteristics make it one of the most important areas in Turkey (Ozyavuz, et al., 2006) (Table Igneada and the surrounding environment have unique characteristics; these types (Igneada Longos Forests)

of wild forest in other parts of Turkey and in Europe have been damaged due to anthropogenic effects (Figure 4)

Fig 4 General view of this area

Typically, flooded alluvial forests have high biological diversity, high productivity, and high habitat dynamism (Hughes et al., 2003) The surface area of these forests is around 3000

ha Igneada alluvial longos forests are part of the Istranca forests; they are indeed ‘‘natural treasures’’ that have been formed by several ecosystems over thousands of years (Özyavuz and Yazgan, 2010)

Resource Value Area (ha.) Main Characteristic

Longos forest 1400 Alluvial flooded forest, rarity, sensitivity, flora, fauna

Wetlands and

marshes

Wetlands (lagoon lake 52) (other 28) Marshes (315)

Geomorphological structure, flora, fauna,

Sand dunes 131 Geomorphological structure, flora (especially endemic plants)

Streams - Naturalness, flora

Deciduous

forests - Naturalness, plant diversity, fauna

Table 4 Resource values of İğneda Longos forests National Park

Protected Areas 15 There are five lakes in the area Lake Erikli Lagoon (43 ha) is adjacent to the northern part of

I gneada subdistrict, which is not linked with the sea during the summer period Lake Mert (266 ha) is located at the southern part of the subdistrict, where the stream reaches the Black Sea Lake Saka, which is the smallest (5 ha), is at the southernmost part of the study area between the forest and sand Lake Hamam (19 ha) and Lake Pedina (10 ha) are located in the inner part The coastal dunes and the longos forests of Igneada constitute the most sensitive

ecosystem in the study area Most of the known endemic plants (Silene sangaria, Crepis macropus, Centaurea kilaea) in Igneada and its vicinity are found in the coastal dunes; other species found here, though not endemics, are of national and international concern (Aurinia uechtritziana, Cakile maritima, Cionura erecta, Crambe maritima, Cyperus capitatus, Elymus elongatus subsp elongatu, Eryngium maritimum, Euphorbia peplis, Eu paralias, Jurinea kilae, Leymus racemosus, Otanthus maritimus, Pancratimum maritimum, Peucedanum obtusifolium, Stachys maritima) (Figure 5-10) (Özyavuz and Yazgan, 2010)

Fig 7 Jurinea kilae

Fig 8 Leymus racemosus

Protected Areas 17

Fig 9 Otanthus maritimus

Fig 10 Pancratimum maritimum

There are three longos forests in the area The conserved natural longos forests in the study area are the Lake Mert longos (316 ha), Lake Erikli longos (456 ha), and Lake Saka longos (624 ha) forests (Figure 11-13) This type of ecosystem is unique and rare in Turkey and the world because these ecosystems are sensitive to environmental conditions In general, deciduous mixed forest vegetation is found in the area outside of the longos forests, and in this area the forests have similar floristic composition to the longos forests However, slopes are rather steep in the area where these forests are found, and therefore the water table is well below the surface The different ecosystems in the area provide a diverse living environment for the fauna in the region Nearly half (194) of the 454 bird species constituting the bird diversity of Turkey are seen in this area during the year (Özyavuz and Yazgan, 2010)

Fig 11 Lake Mert

Fig 12 Lake Erikli

Protected Areas 19

Fig 13 Lake Saka

4 References

Dudley, N (Editor) (2008) Guidelines for Applying Protected Area Management

Categories, International Union for Conservation of Nature and Natural Resources, 86

pp., ISBN 978-2-8317-1086-0, Gland, Switzerland

Güçlü, K., Karahan, F (2004) A review: the history of conservation programs and

development of the national parks concept in Turkey, Biodiversity and Conservation 13: 1373–1390, 2004

IUCN (1994) Guidelines for Protected Area Management Categories, IUCN Commission on

National Parks and Protected Areas with the assistance of the World Conservation Monitoring Centre, pp 5-7, ISBN 2-8317-0201-1, Switzerland and Cambridge, UK

IUCN (2000) Indigenous and Traditional Peoples and Protected Areas, IUCN, Gland,

Switzerland and Cambridge, UK

IUCN (2001) Guidelines for Financing Protected Areas in East Asia, World Commission on

Protected Areas (WCPA), IUCN, Gland, Switzerland, and Cambridge, UK

IUCN (2003) Guidelines for Management Planning of Protected Areas, IUCN, Gland,

Switzerland and Cambridge, UK

Ministry of Environment (2001) The National Strategy and Action Plan for Biodiversity in

Turkey”

Ministry of Environment (2002) National Report on Sustainable Development 2002,

Ministry of Republic of Turkey

Özyavuz, M and Yazgan, M 2010 Planning of Igneada Longos (Flooded) Forests as a

Biosphere Reserve, Journal of Coastal Research, (26)6:1104-1111

Weeks, P and Mehta, S (2004) Managing People and Landscapes: IUCN’s Protected Area

Categories, J Hum Ecol, (16) 4: 253-263

Yücel M (1995) Protected Areas and Planning Publication No 104, C¸ ukurova University

Press, Adana, Turkey, 255 pp (in Turkish)

2

Land Use/Cover Classification Techniques Using Optical Remotely Sensed Data in Landscape Planning

Onur Şatır and Süha Berberoğlu

Cukurova University, Agriculture Faculty, Department of Landscape Architecture,

Turkey

1 Introduction

The observed biophysical cover of the earth’s surface, termed land-cover is composed of patterns that occur due to a variety of natural and human-derived processes On the other hand Land-use is human activity on the land, influenced by economic, cultural, political, historical, and land-tenure factors Remotely-sensed data (i.e., satellite or aerial imagery) can often be used to define land-use through observations of the land-cover (Brown, et al., 2000; Karl & Maurer, 2010) Up-to-date land-use information is of critical importance to planners, scientists, resource managers, and decision makers

Optical remote sensing (RS) plays a vital role about defining LUC (land use/cover) and monitoring interactions between nature and human activities Additionally, RS provides time, energy and cost saving Today, optical RS data such as satellite sensor images and aerial photos are used widely to detect LUC dynamics LUC mapping outcomes are used for global, regional, local mapping, change detection, landscape planning and driving landscape metrics

RS image classification is a complex process and requires consideration of many factors The major steps of image classification may include i) determination of a suitable classification system, ii) image preprocessing iii) selection of training samples, iv) selection of suitable classification approaches and post-classification processing, and v) accuracy assessment Additionally, the user’s need, scale of the study area, economic condition, and analyst’s skills are important factors influencing the selection of remotely sensed data, the design of the classification procedure, and the quality of the classification results (Lu and Weng 2007) LUC mapping has been used for various purposes in landscape planning and assessment such as, deriving landscape metrics (Southworth et al., 2010, Huang et al., 2007), landscape monitoring (Özyavuz et al., 2011, Berberoglu and Akin 2009), LUC change modeling (e.g., SLUETH (Clarke, 2008)), agricultural studies (agricultural policy environmental extender model (APEX) (Gassman et al., 2010); soil water assessment tool (SWAT) (Betrie et al 2011)) and environmental processes (revised universal soil loss equation (RUSLE) (Renard et al., 1997))

This chapter evaluates classification methods together with optical remote sensing data, and ancillary data integration to improve classification accuracy of LUC mapping

2 LUC classification schemes

Standardization is one of the most discussed issues in LUC classification studies, and scientist and map developers were aware that using a common classification schemes might

be more comparable and available The first standardization works started in USA Today there are several LUC schemes on the world according to region and scale This chapter will discuss three largely used schemes; i) USGS (US geological survey) Anderson, ii) CORINE (Coordination of information on the environment) and iii) EUNIS (European Nature Information System) habitat schemes

2.1 USGS Anderson classification schemes

This classification scheme was utilized within large number of models in the context of land physical dynamics and natural risk assessment USGS classification scheme is based on James Anderson’s system This scheme is included nine main categories and four different levels (Anderson et al., 1976)

Level I is suitable for 1/250.000 – 1/150.000 scale imags like MODIS and Envisat MERIS Level II is useful for higher spatial resolution satellite sensor images with a scale of 1:80,000 Level III is suitable for 1:20,000 to 1/80,000 scale images such as, Landsat 4-7 Level IV is the most useful for images at scales larger than 1:20,000 (Ikonos, Kompsat, Rapid eye, Formosat, Geoeye, World view and aerial photos) Categories are designed to be adaptable to the local needs Sample of Level I categories and forest land levels are showed in table 1

42 Coniferous Forest

43 Broadleaved Forest

MixedConifer-421 Upland conifers

422 Lowland conifers

4219 Other

Table 1 USGS classification scheme for level I of forest cover

2.2 CORINE classification scheme

The European council found EEA (European environmental agency) in 1990 to search and discuss the environmental issues all around the Europe LUC of Europe is one of the most

Land Use/Cover Classification Techniques

important data to define environmental strategies CORINE system aims at collecting comparable and consistent land cover data across Europe This information system, offers the essential elements for the applications of nature conservation, urban planning and resource management The European nomenclature distinguishes 44 different types of land cover Individual countries can supplement these categories with a more detailed level if they desire

so CORINE Land Cover is bridging the gap between the local (micro) and the EU (macro) scales CORINE Land Cover is a platform of communication not only for environmental information, but also for the policies that shape the environment (figure 1)

Fig 1 The legend of CORINE LUC classes codes and colors (EEA 2012b)

2.3 EUNIS habitat classification scheme

The EUNIS habitat classification is a common reporting language on habitat types at European level, sponsored by the EEA It originated from a combination of several habitat classifications - marine, terrestrial and freshwater The terrestrial and freshwater classification builds upon previous initiatives, notably the CORINE biotopes classification (Devillers & Devillers-Terschuren 1991), the Palaearctic habitats classification (Devillers & Devillers-Terschuren 1996), of the EU Habitats Directive 92/43/EEC, the CORINE Land

Cover nomenclature (Bossard et al 2000), and the Nordic habitat classification (Nordic Council of Ministers 1994) The marine part of the classification was originally based on the BioMar classification (Connor et al 1997), covering the North-East Atlantic The EUNIS habitat classification introduced agreed criteria for the identification of each habitat unit, while providing a correspondence with these earlier classification systems

The habitat classification forms an integral part of the EUNIS, developed and managed by the European Topic Centre for Nature Protection and Biodiversity (ETC/NPB in Paris) for the EEA and the European Environmental Information Observation Network (EIONET) The EUNIS web application (http://eunis.eea.europa.eu) (EEA 2012a) provides access to publicly available data in a consolidated database

The information includes:

 Data on Species, Habitats and Sites compiled in the framework of NATURA2000 (EU Habitats and Birds Directives),

 Data collected from frameworks such as EIONET, data sources or material published by ETC/NPB (formerly the European Topic Centre for Nature Conservation)

 Information on Species, Habitats and Sites taken into account in relevant international conventions or from International Red Lists

 Specific data collected in the framework of the EEA's reporting activities, which also constitute a core set of data to be updated periodically

The resulting system of classification is still somewhat transitional Down to level 3 (terrestrial and freshwater) and level 4 (marine), EUNIS habitats are now based on physiognomic and physical attributes, together with some floristic criteria There are 10 main habitat categories in this scheme Coastal habitats and main categories as an example were presented in this chapter (table 2) Detailed information can be found in revised EUNIS habitat classification report of Davies et al (2004)

A Marine habitats

B Coastal habitats

C Inland surface waters

D Mires, bogs and fens

E Grasslands and lands dominated

by forbs, mosses or lichens

F Heathland, scrub and tundra

G Woodland, forest and other

wooded land

H Inland unvegetated and sparsely

vegetated habitats

I Regularly or recently cultivated

agricultural, horticultural and

shores, including the supralittoral

B1.1 Sand beach driftlines B1.2 Sand beaches above the driftline

B1.3 Shifting coastal dunes

B1.4 Coastal stable dune grassland (grey dunes) B1.5 Coastal dune heaths B1.6 Coastal dune scrub B1.7 Coastal dune woods B1.8 Moist and wet dune slacks

B1.9 Machair

Table 2 Main EUNIS habitat classes and sample levels of coastal habitats

Land Use/Cover Classification Techniques

3 Remotely sensed data sources

Data characteristics are the most important issue to select appropriate available one for a LUC mapping Both airborne and spaceborne data have various spatial, radiometric, spectral and temporal resolutions Large numbers of studies have focused on characteristics

of remotely sensed data (Barnsley 1999, Lefsky and Cohen 2003) Additionally, scan width (cover size in one scene), data availability (accessibility) and lunch date (data archive potential) are the other important factors (Table 3)

Sensor Organization resolution Spatial resolution Spectral Radiometric resolution resolution Temporal Imaging Swath Lunch date Geoeye Geoeye ABD Pan: 0.41m MS: 0.61m bands (450-4 VNIR

12 bit 5.5 days at nadir 77X77km 2008

World view (2)

and (3)* Digital globe ABD

Pan: 0.5m MS: 2m at nadir

4 VNIR standart bands & 4 VNIR unique bands (400- 1040nm)

11 bit 1-3days 16.4X16.4km 2009 (2) 2014 (3)

Spot 5 SpotIMAGE France VNIR:10m Pan:2.5m

SWIR:20m

3 VNIR & 1 SWIR bands

ASTER Japan&ABD VNIR: 15m SWIR: 30m

TIR: 90m

4 VNIR bands

6 SWIR bands

5 TIR bands (520- 11650nm)

VNIR:8 bit SWIR: 8 bit TIR: 12 bit 16 days 60X60km 1999

Landsat 8* NASA ABD Pan: 15m MS: 30m

5 VNIR bands

2 SWIR bands

1 cirrus band (433-2300nm)

8 bit 16 days 185X185km Dec 2012

CHRIS proba

18-62 VNIR bands (400-

Sensor Organization resolution Spatial resolution Spectral Radiometric resolution resolution Temporal Imaging Swath Lunch date Hyperion

220 VNIR &

SWIR bands (400-2500nm) 16 bit 16 days 7.7X185km 2000 EnMAP* DLR Germany 30m 244 VNIR & SWIR bands

2014-2015

MODIS NASA ABD 250-1000m SWIR & TIR 36 VNIR &

AVHRR

NOAA 15 NASA ABD 1090m TIR bands 6 VNIR & 10 bit 1 day 1446km 1978 1998

Table 3 The most used optical sensor specifications in LUC mapping (*) planned missions

4 LUC mapping techniques

Suitable remotely sensed data, classification systems, available classifier and number of training samples are prerequisites for a successful classification Cingolani et al (2004) identified three major problems when medium spatial resolution data are used for vegetation classifications: i) defining adequate hierarchical levels for mapping, ii) defining discrete land-cover units discernible by selected remote-sensing data, and iii) selecting representative training sites In general, a classification system is designed based on the user’s need, spatial resolution of selected remotely sensed data, compatibility with previous work, image-processing and classification algorithms, and time constraints Such a system should be informative, exhaustive, and separable (Jensen 1996, Landgrebe 2003) In many cases, a hierarchical classification system

is adopted to take different conditions into account (Lu and Weng 2007)

4.1 Image pre-processing

Image pre-processing includes geometric correction or image registration, atmospheric correction and radiometric calibration essentially In addition, topographic correction and noise reduction may be applied if necessary Optical images from current systems have already corrected geometrically (Landsat TM/ETM, MODIS) or can be corrected using freely available software or tools (e.g BEAM for MERIS and CHRIS and MRT toolbox for MODIS) Accurate geometric rectification or image registration of remotely sensed data is a prerequisite for a combination of different source data in a classification process Many textbooks and articles have described this topic in detail (Jensen 1996, Toutin 2004) However, Geometric correction output should have the transformation rms errors (RMSE) less than 1.0 pixel, indicating that the images are located with an accuracy of less than a pixel

Atmospheric and radiometric corrections may not be necessary if a single image is used, but multitemporal or multisensor data are needed atmospheric and radiometric correction and calibration A variety of methods, ranging from simple relative calibration such as, dark-object subtraction to calibration approaches based on complex models (e.g MODTRAN, 6S,

Land Use/Cover Classification Techniques

ATCOR2), have been developed for radiometric and atmospheric normalization and correction (Chavez 1996, Heo and FitzHugh 2000, Hadjimitsis et al 2004, Ozyavuz et al 2011) (Figure 2)

Fig 2 (a) Non-corrected data, (b) Atmospherically corrected and haze removed Landsat

TM data using ATCOR2 model (Özyavuz et al 2011)

4.2 Classification techniques

There are two basic approaches to the classification process: supervised and unsupervised classification With supervised classification, one provides a statistical description of the manner in which expected land cover classes should appear in the imagery, and then a procedure (known as a classifier) is used to evaluate the likelihood that each pixel belongs to one of these classes With unsupervised classification, a very different approach is used Here another type of classifier is used to uncover commonly occurring and distinctive reflectance patterns in the imagery, on the assumption that these represent major land cover classes The analyst then determines the identity of each class by a combination of experience and ground truth (i.e., visiting the study area and observing the actual cover types) (Eastman 2003) Three essential parts are vital in a LUC mapping in classification stage; training, classifying and testing (accuracy assessment)

4.2.1 Classifiers

In this chapter four different classifiers and approaches were evaluated in the example of Landsat TM sub-scenes recorded over Eastern Mediterranean coastal part Methods and performances were assessed based on accuracy, capability and applicability This assessment covered traditional (minimum distance, maximum likelihood, linear discriminant analyses), machine learning (decision tree, artificial neural network, support vector machine), fuzzy (linear mixture modeling, fuzzy c-means, artificial neural network, regression tree) and object based classifiers for LUC mapping The summary of the techniques and classifiers for various purposes were provided in table 4

Criteria Categories Characteristics Example of

Land cover classes are defined

Sufficient reference data are available and used as training samples The signatures generated from the training samples are then used to train the classifier to classify the spectral data into a thematic map

Maximum likelihood (MLC), minimum distance (MD), Artificial neural network (ANN), decision tree (DT) classifier

Unsupervised

classification approaches

Clustering-based algorithms are used

to partition the spectral image into a number of spectral classes based on the statistical information inherent in the image No prior definitions of the classes are used The analyst is responsible for labeling and merging the spectral classes into meaningful classes

ISODATA, K-means clustering algorithm

Gaussian distribution is assumed The parameters (e.g mean vector and covariance matrix) are often generated from training samples When landscape is complex, parametric classifiers often produce ‘noisy’ results

Another major drawback is that it is difficult to integrate ancillary data, spatial and contextual attributes, and non-statistical information into a classification procedure

MLC and Linear discriminant analysis (LDA)

Non-parametric classifiers

No assumption about the data is required Non-parametric classifiers do not employ statistical parameters to calculate class separation and are especially suitable for incorporation of non-remote-sensing data into a classification procedure

ANN, DT, Support vector machine (SVM), evidential reasoning, expert system

Traditional classifiers typically develop

a signature by combining the spectra of all training-set pixels from a given feature The resulting signature contains the contributions of all materials present in the training-set pixels, ignoring the mixed pixel problems

MLC, MD, SVM, ANN, DT

Subpixel

classifiers

The spectral value of each pixel is assumed to be a linear or non-linear combination of defined pure materials (or endmembers), providing

proportional membership of each pixel

to each endmember

Fuzzy-set classifiers, subpixel classifier, spectral mixture analysis